Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Compiling specificity into approaches to nonmonotonic reasoning
Artificial Intelligence
Knowledge Representation, Reasoning, and Declarative Problem Solving
Knowledge Representation, Reasoning, and Declarative Problem Solving
A Maximum Entropy Approach to Nonmonotonic Reasoning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Compiling Default Theory int Extended Logic Programming
IBERAMIA-SBIA '00 Proceedings of the International Joint Conference, 7th Ibero-American Conference on AI: Advances in Artificial Intelligence
Adding Priorities and Specificity to Default Logic
JELIA '94 Proceedings of the European Workshop on Logics in Artificial Intelligence
Defeasible logic programming: an argumentative approach
Theory and Practice of Logic Programming
System Z: a natural ordering of defaults with tractable applications to nonmonotonic reasoning
TARK '90 Proceedings of the 3rd conference on Theoretical aspects of reasoning about knowledge
Handling uncertainty and defeasibility in a possibilistic logic setting
International Journal of Approximate Reasoning
Dealing Automatically with Exceptions by Introducing Specificity in ASP
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A clash of intuitions: the current state of nonmonotonic multiple inheritance systems
IJCAI'87 Proceedings of the 10th international joint conference on Artificial intelligence - Volume 1
Answer set programming for computing decisions under uncertainty
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Answer set programming for computing decisions under uncertainty
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Nested Preferences in Answer Set Programming
Fundamenta Informaticae - Latin American Workshop on Logic Languages, Algorithms and New Methods of Reasoning (LANMR)
Dealing with explicit preferences and uncertainty in answer set programming
Annals of Mathematics and Artificial Intelligence
Using possibilistic logic for modeling qualitative decision: Answer Set Programming algorithms
International Journal of Approximate Reasoning
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Default rules, i.e. statements of the form normally a's are b's, are usually handled in Answer Set Programming by means of negation as failure which provides a way to capture exceptions to normal situations. In this paper we propose another approach which offers an operational counterpart to negation as failure, and which may be thought as a corresponding dual attitude. The approach amounts to an explicit rewriting of exceptions in default rules, together with the addition of completion rules that are consistent with current knowledge. It is shown that the approach can be applied to restore the consistency of inconsistent programs that implicitly involve specificity ordering between the rules. The approach is compared to previous works aiming at providing support to the rewriting of default rules. It is also shown how the proposed approach agrees with the results obtained in the classical way.